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Transient Modeling of Induction Machine Using Artificial Neural Network Surrogate Models

Year of publication

2022

Authors

Tahkola, Mikko; Mukherjee, Victor; Keränen, Janne

Abstract

<p>A transient model of an induction machine (IM) is developed in this work using an artificial neural network (ANN) surrogate model. The model is suitable to be used for direct-on-line IMs. The finite-element (FE)-based model of IM is used to generate the training, validation, and testing datasets. Different inputs and model configurations are investigated to find an optimal solution in developing the transient model. The proposed transient model is suitable to be used in digital twin services since it can estimate the current and torque accurately in real time based on only voltage and measured shaft speed.</p>
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Organizations and authors

VTT Technical Research Centre of Finland Ltd

Keränen Janne Orcid -palvelun logo

Tahkola Mikko Orcid -palvelun logo

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Journal

IEEE Transactions on Magnetics

Volume

58

Issue

9

Article number

7402204

ISSN

0018-9464

​Publication forum

57556

​Publication forum level

1

Open access

Open access in the publisher’s service

Yes

Open access of publication channel

Partially open publication channel

License of the publisher’s version

CC BY

Self-archived

No

Other information

Fields of science

Electronic, automation and communications engineering, electronics

Keywords

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Language

English

International co-publication

No

Co-publication with a company

Yes

DOI

10.1109/TMAG.2022.3180176

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes